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Moderate- and large-deviation probabilities in actuarial risk theory

Published online by Cambridge University Press:  01 July 2016

Eric Slud*
Affiliation:
University of Maryland
Craig Hoesman*
Affiliation:
U.S. Department of Defence
*
Postal address: Statistics Program, Mathematics Department, University of Maryland, College Park, MD 20742, USA.
∗∗Permanent address: Special U.S. Liaison Officer, Box 5000, U.S. Embassy, Ogdensburg, NY 13669-0430, USA.

Abstract

A general model for the actuarial risk-reserve process as a superposition of compound delayed-renewal processes is introduced and related to previous models which have been used in collective risk theory. It is observed that non-stationarity of the portfolio ‘age-structure' within this model can have a significant impact upon probabilities of ruin. When the portfolio size is constant and the policy age-distribution is stationary, the moderate- and large-deviation probabilities of ruin are bounded and calculated using the strong approximation results of Csörg et al. (1987a, b) and a large-deviation theorem of Groeneboom et al. (1979). One consequence is that for non-Poisson claim-arrivals, the large-deviation probabilities of ruin are noticeably affected by the decision to model many parallel policy lines in place of one line with correspondingly faster claim-arrivals.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 1989 

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Footnotes

Research supported by Office of Naval Research under contract ONR-86-K-0007.

References

Bahadur, R. (1971) Some Limit Theorems in Statistics. SIAM, Philadelphia.Google Scholar
Barlett, M. (1946) The large-sample theory of sequential tests. Proc. Camb. Phil. Soc. 42, 239244.CrossRefGoogle Scholar
Beekman, J. (1974) Two Stochastic Processes. Halsted Press, New York.Google Scholar
Chernoff, H. (1952) A measure of asymptotic efficiency for tests for a hypothesis based on the sum of observations. Ann. Math. Statist. 23, 493507.CrossRefGoogle Scholar
Cramer, H. (1955) Collective risk theory: A survey of the theory from the point of view of the theory of stochastic processes. In The Jubilee Volume of Skandia Insurance Company, Stockholm, 192.Google Scholar
Csörgõ, M., Deheuvels, P. and Horvath, L. (1978a) An approximation of stopped sums with applications in queueing theory. Adv. Appl. Prob. 19, 674690.Google Scholar
Csörgõ, M., Horvath, L. and Steinebach, J. (1987b) Invariance principles for renewal processes. Ann. Prob. 15, 14411460.Google Scholar
Dassios, A. and Embrechts, P. (1987) Martingales and insurance risk. Stoch. Models. To appear.Google Scholar
Durbin, J. (1985) The first-passage density of a Gaussian process to a curved boundary. J. Appl. Prob. 22, 99122.Google Scholar
Groeneboom, P., Oosterhoff, J. and Ruymgaart, F. (1979) Large deviations theorems for empirical probability measures. Ann. Prob. 7, 553586.Google Scholar
Harrison, L. (1977) Ruin problems with compounding asserts. Stoch. Proc. Appl. 5, 6769.Google Scholar
Horvath, L. and Willekens, E. (1986) Estimates for probability of ruin starting with large initial reserve. Insurance: Math. Econ. 5, 285293.Google Scholar
Iglehart, D. (1969) Diffusion approximations in collective risk theory. J. Appl. Prob. 6, 285292.Google Scholar
Karlin, S. and Taylor, H. (1975) A First Course in Stochastic Processes, 2nd edn. Academic Press, New York.Google Scholar
Lynch, J. and Sethuraman, J. (1987) Large deviations for processes with independent increments. Ann. Prob. 15, 610627.Google Scholar
Moriconi, F. (1985) Ruin theory under the submartingale assumption. In NATO Adv. Study Inst. Insurance and Risk Theory, Ser. C, Vol. 171.Google Scholar
Petrov, V. (1972) Sums of Independent Random Variables. Springer-Verlag, Berlin.Google Scholar
Slud, E. (1989) Martingale Methods in Statistics.Google Scholar
Stroock, D. W. (1984) An Introduction to the Theory of Large Deviations. Springer-Verlag, New York.Google Scholar
Thorin, O. (1982) Probabilities of ruin. Scand. Actuar. J., 65102.Google Scholar